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A Lagrangian relaxation-based heuristic for the vehicle routing with full container load

机译:基于拉格朗日松弛法的满载集装箱路线

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We address a problem of vehicle routing that arises in picking up and delivering full container load from/to an intermodal terminal. The substantial cost and time savings are expected by efficient linkage between pickup and delivery tasks, if the time of tasks and the suitability of containers for cargo allow. As this problem is NP-hard, we develop a subgradient heuristic based on a Lagrangian relaxation which enables us to identify a near optimal solution. The heuristic consists of two sub-problems: the classical assignment problem and the generalized assignment problem. As generalized assignment problem is also NP-hard, we employ an efficient solution procedure for a bin packing based problem, which replaces the generalized assignment problem. The heuristic procedure is tested on a wide variety of problem examples. The test results demonstrate that the procedure developed here can efficiently solve large instances of the problem. (c) 2005 Elsevier B.V. All rights reserved.
机译:我们解决了在多式联运码头提取/交付全部集装箱货物时出现的车辆路线安排问题。如果任务时间和货物集装箱的适用性允许,则可以通过有效地将取货和交付任务联系起来,从而节省大量的成本和时间。由于此问题是NP难题,因此我们基于Lagrangian弛豫开发了次梯度启发式算法,使我们能够确定接近最佳的解决方案。启发式方法包含两个子问题:经典分配问题和广义分配问题。由于广义分配问题也是NP难的,因此我们针对基于bin打包的问题采用了有效的求解过程,从而代替了广义分配问题。启发式过程在各种各样的问题示例中进行了测试。测试结果表明,此处开发的过程可以有效解决问题的大量实例。 (c)2005 Elsevier B.V.保留所有权利。

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